中文摘要：

为准确对采煤工作面煤与瓦斯突出危险性进行智能判识,在充分考虑采掘工程扰动因素对煤与瓦斯突出动态影响的基础上,选取瓦斯含量、瓦斯压力、采动应力、地质构造等因素作为采煤工作面煤与瓦斯突出的主要影响因素,结合矿山压力与瓦斯抽采理论,提出影响因素的动态计算方法;运用人工神经网络和多因素模式识别方法,建立煤与瓦斯突出的智能判识模型;应用VBA编程技术以Auto CAD为平台开发工作面煤与瓦斯突出危险性智能判识系统,实现工作面回采过程中各区域突出危险性的动态预测和分级管理。平顶山十二矿己15-17200工作面的现场实际应用表明,预测结果总体趋势与现场实际有较好的一致性。

英文摘要：

In order to accurately determine the risk of coal and gas outburst in coal mining face influences of mining engineering activities on coal and gas outburst were fully considered, gas（methane） content, gas pressure, geologic structure, mining stress were identified as the main factors affecting coal and gas outburst. A dynamic method was worked out for calculation of dynamic influence factors based on theory of mine pressure and gas drainage. Using the artificial neural network and multivariate pattern recognition, identification criteria and a model were established. After that, a coal and gas outburst risk intelligence recognition system was developed, which is based on Auto CAD and VBA. As the working face advancing, the system can be used easily and dynamically to predict and manage the risk values for working areas. Combined with the actual situation in Pingdingshan No.12 coal mine, the risk in working face Ji15-17200 was predicted. Compared with the scene, the overall trend of prediction results conforms with the reality.